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| pip install gradio openai | |
| import openai | |
| import gradio as gr | |
| # Set your LLaMA3 API key | |
| openai.api_key = 'your-llama3-api-key' | |
| def ai_developer_agent(prompt, specialization="general"): | |
| """ | |
| Function to interact with the LLaMA3 API and get a response based on the prompt and specialization. | |
| :param prompt: The input text to the AI agent. | |
| :param specialization: The area of specialization for the AI agent. | |
| :return: The response from the AI agent. | |
| """ | |
| try: | |
| specialized_prompt = ( | |
| f"You are an AI developer assistant specializing in {specialization}. " | |
| "Answer the following query or provide the requested code snippet:\n\n{prompt}" | |
| ) | |
| response = openai.Completion.create( | |
| engine="text-davinci-003", | |
| prompt=specialized_prompt, | |
| max_tokens=300, | |
| n=1, | |
| stop=None, | |
| temperature=0.7 | |
| ) | |
| return response.choices[0].text.strip() | |
| except Exception as e: | |
| return str(e) | |
| def determine_specialization(query): | |
| """ | |
| Function to determine the specialization based on the query content. | |
| :param query: The input query from the user. | |
| :return: The determined area of specialization. | |
| """ | |
| if "frontend" in query.lower(): | |
| return "frontend development" | |
| elif "backend" in query.lower(): | |
| return "backend development" | |
| elif "debug" in query.lower(): | |
| return "debugging" | |
| elif "deploy" in query.lower(): | |
| return "deployment" | |
| else: | |
| return "general development" | |
| def interact(query): | |
| specialization = determine_specialization(query) | |
| response = ai_developer_agent(query, specialization) | |
| return response | |
| iface = gr.Interface( | |
| fn=interact, | |
| inputs="text", | |
| outputs="text", | |
| title="AI Developer Agent", | |
| description="Ask the AI developer assistant anything about frontend, backend, debugging, or deployment." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |
| python ai_developer_agent.py | |
| from flask import Flask, jsonify, request | |
| app = Flask(__name__) | |
| def get_api(): | |
| data = {"message": "Hello, World!"} | |
| return jsonify(data) | |
| def post_api(): | |
| data = request.get_json() | |
| return jsonify(data), 201 | |
| if __name__ == '__main__': | |
| app.run(debug=True) | |
| import pdb | |
| def add(a, b): | |
| pdb.set_trace() # This will pause execution and open the debugger | |
| return a + b | |
| result = add(3, 5) | |
| print(result) | |